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    Transcribe audio from a video file using Speech-to-Text

    This tutorial shows how to transcribe the audio track from a video file using Speech-to-Text.

    Audio files can come from many different sources. Audio data can come from a phone (like voicemail) or the soundtrack included in a video file.

    Speech-to-Text can use one of several machine learning models to transcribe your audio file, to best match the original source of the audio. You can get better results from your speech transcription by specifying the source of the original audio. This allows Speech-to-Text to process your audio files using a machine learning model trained for data similar to your audio file.

    Objectives

    • Send a audio transcription request for a video file to Speech-to-Text.

    Costs

    In this document, you use the following billable components of Google Cloud:

    • Speech-to-Text

    To generate a cost estimate based on your projected usage, use the pricing calculator .

    New Google Cloud users might be eligible for a free trial .

    Before you begin

    This tutorial has several prerequisites:

    Prepare the audio data

    Before you can transcribe audio from a video, you must extract the data from the video file. After you've extracted the audio data, you must store it in a Cloud Storage bucket or convert it to base64-encoding.

    Extract the audio data

    You can use any file conversion tool that handles audio and video files, such as FFmpeg .

    Use the code snippet below to convert a video file to an audio file using ffmpeg .

    ffmpeg  
-i  
 video-input-file 
  
 audio-output-file

    Store or convert the audio data

    You can transcribe an audio file stored on your local machine or in a Cloud Storage bucket .

    Use the following command to upload your audio file to an existing Cloud Storage bucket using the Google Cloud CLI .

    gcloud  
storage  
cp  
 audio-output-file 
  
 storage-bucket-uri

    If you use a local file and plan to send a request using the curl tool from the command line, you must convert the audio file to base64-encoded data first.

    Use the following command to convert an audio file to a text file.

    base64  
 audio-output-file 
  
-w  
 0 
  
>  
 audio-data-text

    Send a transcription request

    Use the following code to send a transcription request to Speech-to-Text.

    Local file request

    Protocol

    Refer to the speech:recognize API endpoint for complete details.

    To perform synchronous speech recognition, make a POST request and provide the appropriate request body. The following shows an example of a POST request using curl . The example uses the Google Cloud CLI to generate an access token. For instructions on installing the gcloud CLI, see the quickstart .

    curl  
-s  
-H  
 "Content-Type: application/json" 
  
 \ 
  
-H  
 "Authorization: Bearer 
 $( 
gcloud  
auth  
application-default  
print-access-token ) 
 " 
  
 \ 
  
https://speech.googleapis.com/v1/speech:recognize  
 \ 
  
--data  
 '{ 
 "config": { 
 "encoding": "LINEAR16", 
 "sampleRateHertz": 16000, 
 "languageCode": "en-US", 
  "model": "video" 
 }, 
 "audio": { 
 "uri": "gs://cloud-samples-tests/speech/Google_Gnome.wav" 
 } 
 }'

    See the RecognitionConfig reference documentation for more information on configuring the request body.

    If the request is successful, the server returns a 200 OK HTTP status code and the response in JSON format:

    {
  "results": [
    {
      "alternatives": [
        {
          "transcript": "OK Google stream stranger things from
            Netflix to my TV okay stranger things from
            Netflix playing on TV from the people that brought you
            Google home comes the next evolution of the smart home
            and it's just outside your window me Google know hi
            how can I help okay no what's the weather like outside
            the weather outside is sunny and 76 degrees he's right
            okay no turn on the hose I'm holding sure okay no I'm can
            I eat this lemon tree leaf yes what about this Daisy yes
            but I wouldn't recommend it but I could eat it okay
            Nomad milk to my shopping list I'm sorry that sounds like
            an indoor request I keep doing that sorry you do keep
            doing that okay no is this compost really we're all
            compost if you think about it pretty much everything is
            made up of organic matter and will return",
          "confidence": 0.9251011
        }
      ]
    }
  ]
}

    Go

    To learn how to install and use the client library for Speech-to-Text, see Speech-to-Text client libraries . For more information, see the Speech-to-Text Go API reference documentation .

    To authenticate to Speech-to-Text, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      func 
  
 modelSelection 
 ( 
 w 
  
 io 
 . 
 Writer 
 ) 
  
 error 
  
 { 
  
 ctx 
  
 := 
  
 context 
 . 
 Background 
 () 
  
 client 
 , 
  
 err 
  
 := 
  
 speech 
 . 
 NewClient 
 ( 
 ctx 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "NewClient: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 defer 
  
 client 
 . 
 Close 
 () 
  
 data 
 , 
  
 err 
  
 := 
  
 os 
 . 
 ReadFile 
 ( 
 "../testdata/Google_Gnome.wav" 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "ReadFile: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 req 
  
 := 
  
& speechpb 
 . 
 RecognizeRequest 
 { 
  
 Config 
 : 
  
& speechpb 
 . 
 RecognitionConfig 
 { 
  
 Encoding 
 : 
  
 speechpb 
 . 
 RecognitionConfig_LINEAR16 
 , 
  
 SampleRateHertz 
 : 
  
 16000 
 , 
  
 LanguageCode 
 : 
  
 "en-US" 
 , 
  
 Model 
 : 
  
 "video" 
 , 
  
 }, 
  
 Audio 
 : 
  
& speechpb 
 . 
 RecognitionAudio 
 { 
  
 AudioSource 
 : 
  
& speechpb 
 . 
 RecognitionAudio_Content 
 { 
 Content 
 : 
  
 data 
 }, 
  
 }, 
  
 } 
  
 resp 
 , 
  
 err 
  
 := 
  
 client 
 . 
 Recognize 
 ( 
 ctx 
 , 
  
 req 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "recognize: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 for 
  
 i 
 , 
  
 result 
  
 := 
  
 range 
  
 resp 
 . 
 Results 
  
 { 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "%s\n" 
 , 
  
 strings 
 . 
 Repeat 
 ( 
 "-" 
 , 
  
 20 
 )) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Result %d\n" 
 , 
  
 i 
 + 
 1 
 ) 
  
 for 
  
 j 
 , 
  
 alternative 
  
 := 
  
 range 
  
 result 
 . 
 Alternatives 
  
 { 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Alternative %d: %s\n" 
 , 
  
 j 
 + 
 1 
 , 
  
 alternative 
 . 
 Transcript 
 ) 
  
 } 
  
 } 
  
 return 
  
 nil 
 }

    Java

    To learn how to install and use the client library for Speech-to-Text, see Speech-to-Text client libraries . For more information, see the Speech-to-Text Java API reference documentation .

    To authenticate to Speech-to-Text, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      /** 
 * Performs transcription of the given audio file synchronously with the selected model. 
 * 
 * @param fileName the path to a audio file to transcribe 
 */ 
 public 
  
 static 
  
 void 
  
 transcribeModelSelection 
 ( 
 String 
  
 fileName 
 ) 
  
 throws 
  
 Exception 
  
 { 
  
 Path 
  
 path 
  
 = 
  
 Paths 
 . 
 get 
 ( 
 fileName 
 ); 
  
 byte 
 [] 
  
 content 
  
 = 
  
 Files 
 . 
 readAllBytes 
 ( 
 path 
 ); 
  
 try 
  
 ( 
 SpeechClient 
  
 speech 
  
 = 
  
 SpeechClient 
 . 
 create 
 ()) 
  
 { 
  
 // Configure request with video media type 
  
 RecognitionConfig 
  
 recConfig 
  
 = 
  
 RecognitionConfig 
 . 
 newBuilder 
 () 
  
 // encoding may either be omitted or must match the value in the file header 
  
 . 
 setEncoding 
 ( 
 AudioEncoding 
 . 
 LINEAR16 
 ) 
  
 . 
 setLanguageCode 
 ( 
 "en-US" 
 ) 
  
 // sample rate hertz may be either be omitted or must match the value in the file 
  
 // header 
  
 . 
 setSampleRateHertz 
 ( 
 16000 
 ) 
  
 . 
 setModel 
 ( 
 "video" 
 ) 
  
 . 
 build 
 (); 
  
 RecognitionAudio 
  
 recognitionAudio 
  
 = 
  
 RecognitionAudio 
 . 
 newBuilder 
 (). 
 setContent 
 ( 
 ByteString 
 . 
 copyFrom 
 ( 
 content 
 )). 
 build 
 (); 
  
 RecognizeResponse 
  
 recognizeResponse 
  
 = 
  
 speech 
 . 
 recognize 
 ( 
 recConfig 
 , 
  
 recognitionAudio 
 ); 
  
 // Just print the first result here. 
  
 SpeechRecognitionResult 
  
 result 
  
 = 
  
 recognizeResponse 
 . 
 getResultsList 
 (). 
 get 
 ( 
 0 
 ); 
  
 // There can be several alternative transcripts for a given chunk of speech. Just use the 
  
 // first (most likely) one here. 
  
 SpeechRecognitionAlternative 
  
 alternative 
  
 = 
  
 result 
 . 
 getAlternativesList 
 (). 
 get 
 ( 
 0 
 ); 
  
 System 
 . 
 out 
 . 
 printf 
 ( 
 "Transcript : %s\n" 
 , 
  
 alternative 
 . 
 getTranscript 
 ()); 
  
 } 
 }

    Node.js

    To learn how to install and use the client library for Speech-to-Text, see Speech-to-Text client libraries . For more information, see the Speech-to-Text Node.js API reference documentation .

    To authenticate to Speech-to-Text, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      // Imports the Google Cloud client library for Beta API 
 /** 
 * TODO(developer): Update client library import to use new 
 * version of API when desired features become available 
 */ 
 const 
  
 speech 
  
 = 
  
 require 
 ( 
 ' @google-cloud/speech 
' 
 ). 
 v1p1beta1 
 ; 
 const 
  
 fs 
  
 = 
  
 require 
 ( 
 'fs' 
 ); 
 // Creates a client 
 const 
  
 client 
  
 = 
  
 new 
  
 speech 
 . 
  SpeechClient 
 
 (); 
 /** 
 * TODO(developer): Uncomment the following lines before running the sample. 
 */ 
 // const filename = 'Local path to audio file, e.g. /path/to/audio.raw'; 
 // const model = 'Model to use, e.g. phone_call, video, default'; 
 // const encoding = 'Encoding of the audio file, e.g. LINEAR16'; 
 // const sampleRateHertz = 16000; 
 // const languageCode = 'BCP-47 language code, e.g. en-US'; 
 const 
  
 config 
  
 = 
  
 { 
  
 encoding 
 : 
  
 encoding 
 , 
  
 sampleRateHertz 
 : 
  
 sampleRateHertz 
 , 
  
 languageCode 
 : 
  
 languageCode 
 , 
  
 model 
 : 
  
 model 
 , 
 }; 
 const 
  
 audio 
  
 = 
  
 { 
  
 content 
 : 
  
 fs 
 . 
 readFileSync 
 ( 
 filename 
 ). 
 toString 
 ( 
 'base64' 
 ), 
 }; 
 const 
  
 request 
  
 = 
  
 { 
  
 config 
 : 
  
 config 
 , 
  
 audio 
 : 
  
 audio 
 , 
 }; 
 // Detects speech in the audio file 
 const 
  
 [ 
 response 
 ] 
  
 = 
  
 await 
  
 client 
 . 
 recognize 
 ( 
 request 
 ); 
 const 
  
 transcription 
  
 = 
  
 response 
 . 
 results 
  
 . 
 map 
 ( 
 result 
  
 = 
>  
 result 
 . 
 alternatives 
 [ 
 0 
 ]. 
 transcript 
 ) 
  
 . 
 join 
 ( 
 '\n' 
 ); 
 console 
 . 
 log 
 ( 
 'Transcription: ' 
 , 
  
 transcription 
 );

    Python

    To learn how to install and use the client library for Speech-to-Text, see Speech-to-Text client libraries . For more information, see the Speech-to-Text Python API reference documentation .

    To authenticate to Speech-to-Text, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      from 
  
 google.cloud 
  
 import 
 speech 
 # Instantiates a client 
 client 
 = 
 speech 
 . 
 SpeechClient 
 () 
 # Reads a file as bytes 
 with 
 open 
 ( 
 "resources/Google_Gnome.wav" 
 , 
 "rb" 
 ) 
 as 
 f 
 : 
 audio_content 
 = 
 f 
 . 
 read 
 () 
 audio 
 = 
 speech 
 . 
  RecognitionAudio 
 
 ( 
 content 
 = 
 audio_content 
 ) 
 config 
 = 
 speech 
 . 
  RecognitionConfig 
 
 ( 
 encoding 
 = 
 speech 
 . 
 RecognitionConfig 
 . 
 AudioEncoding 
 . 
 LINEAR16 
 , 
 sample_rate_hertz 
 = 
 16000 
 , 
 language_code 
 = 
 "en-US" 
 , 
 model 
 = 
 "video" 
 , 
 # Chosen model 
 ) 
 response 
 = 
 client 
 . 
  recognize 
 
 ( 
 config 
 = 
 config 
 , 
 audio 
 = 
 audio 
 ) 
 for 
 i 
 , 
 result 
 in 
 enumerate 
 ( 
 response 
 . 
 results 
 ): 
 alternative 
 = 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 print 
 ( 
 "-" 
 * 
 20 
 ) 
 print 
 ( 
 f 
 "First alternative of result 
 { 
 i 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Transcript: 
 { 
 alternative 
 . 
 transcript 
 } 
 " 
 )

    Additional languages

    C#: Please follow the C# setup instructions on the client libraries page and then visit the Speech-to-Text reference documentation for .NET.

    PHP: Please follow the PHP setup instructions on the client libraries page and then visit the Speech-to-Text reference documentation for PHP.

    Ruby: Please follow the Ruby setup instructions on the client libraries page and then visit the Speech-to-Text reference documentation for Ruby.

    Remote file request

    Go

    To learn how to install and use the client library for Speech-to-Text, see Speech-to-Text client libraries . For more information, see the Speech-to-Text Go API reference documentation .

    To authenticate to Speech-to-Text, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      import 
  
 ( 
  
 "context" 
  
 "fmt" 
  
 "io" 
  
 "strings" 
  
 speech 
  
 "cloud.google.com/go/speech/apiv1" 
  
 "cloud.google.com/go/speech/apiv1/speechpb" 
 ) 
 // transcribe_model_selection_gcs Transcribes the given audio file asynchronously with 
 // the selected model. 
 func 
  
 transcribe_model_selection_gcs 
 ( 
 w 
  
 io 
 . 
 Writer 
 ) 
  
 error 
  
 { 
  
 ctx 
  
 := 
  
 context 
 . 
 Background 
 () 
  
 client 
 , 
  
 err 
  
 := 
  
 speech 
 . 
  NewClient 
 
 ( 
 ctx 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "NewClient: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 defer 
  
 client 
 . 
 Close 
 () 
  
 audio 
  
 := 
  
& speechpb 
 . 
 RecognitionAudio 
 { 
  
 AudioSource 
 : 
  
& speechpb 
 . 
 RecognitionAudio_Uri 
 { 
 Uri 
 : 
  
 "gs://cloud-samples-tests/speech/Google_Gnome.wav" 
 }, 
  
 } 
  
 // The speech recognition model to use 
  
 // See, https://cloud.google.com/speech-to-text/docs/speech-to-text-requests#select-model 
  
 recognitionConfig 
  
 := 
  
& speechpb 
 . 
 RecognitionConfig 
 { 
  
 Encoding 
 : 
  
 speechpb 
 . 
  RecognitionConfig_LINEAR16 
 
 , 
  
 SampleRateHertz 
 : 
  
 16000 
 , 
  
 LanguageCode 
 : 
  
 "en-US" 
 , 
  
 Model 
 : 
  
 "video" 
 , 
  
 } 
  
 longRunningRecognizeRequest 
  
 := 
  
& speechpb 
 . 
 LongRunningRecognizeRequest 
 { 
  
 Config 
 : 
  
 recognitionConfig 
 , 
  
 Audio 
 : 
  
 audio 
 , 
  
 } 
  
 operation 
 , 
  
 err 
  
 := 
  
 client 
 . 
 LongRunningRecognize 
 ( 
 ctx 
 , 
  
 longRunningRecognizeRequest 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "error running recognize %w" 
 , 
  
 err 
 ) 
  
 } 
  
 response 
 , 
  
 err 
  
 := 
  
 operation 
 . 
  Wait 
 
 ( 
 ctx 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 err 
  
 } 
  
 for 
  
 i 
 , 
  
 result 
  
 := 
  
 range 
  
 response 
 . 
 Results 
  
 { 
  
 alternative 
  
 := 
  
 result 
 . 
 Alternatives 
 [ 
 0 
 ] 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "%s\n" 
 , 
  
 strings 
 . 
 Repeat 
 ( 
 "-" 
 , 
  
 20 
 )) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "First alternative of result %d" 
 , 
  
 i 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Transcript: %s" 
 , 
  
 alternative 
 . 
 Transcript 
 ) 
  
 } 
  
 return 
  
 nil 
 }

    Java

    To learn how to install and use the client library for Speech-to-Text, see Speech-to-Text client libraries . For more information, see the Speech-to-Text Java API reference documentation .

    To authenticate to Speech-to-Text, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      /** 
 * Performs transcription of the remote audio file asynchronously with the selected model. 
 * 
 * @param gcsUri the path to the remote audio file to transcribe. 
 */ 
 public 
  
 static 
  
 void 
  
 transcribeModelSelectionGcs 
 ( 
 String 
  
 gcsUri 
 ) 
  
 throws 
  
 Exception 
  
 { 
  
 try 
  
 ( 
 SpeechClient 
  
 speech 
  
 = 
  
 SpeechClient 
 . 
 create 
 ()) 
  
 { 
  
 // Configure request with video media type 
  
 RecognitionConfig 
  
 config 
  
 = 
  
 RecognitionConfig 
 . 
 newBuilder 
 () 
  
 // encoding may either be omitted or must match the value in the file header 
  
 . 
 setEncoding 
 ( 
 AudioEncoding 
 . 
 LINEAR16 
 ) 
  
 . 
 setLanguageCode 
 ( 
 "en-US" 
 ) 
  
 // sample rate hertz may be either be omitted or must match the value in the file 
  
 // header 
  
 . 
 setSampleRateHertz 
 ( 
 16000 
 ) 
  
 . 
 setModel 
 ( 
 "video" 
 ) 
  
 . 
 build 
 (); 
  
 RecognitionAudio 
  
 audio 
  
 = 
  
 RecognitionAudio 
 . 
 newBuilder 
 (). 
 setUri 
 ( 
 gcsUri 
 ). 
 build 
 (); 
  
 // Use non-blocking call for getting file transcription 
  
 OperationFuture<LongRunningRecognizeResponse 
 , 
  
 LongRunningRecognizeMetadata 
>  
 response 
  
 = 
  
 speech 
 . 
 longRunningRecognizeAsync 
 ( 
 config 
 , 
  
 audio 
 ); 
  
 while 
  
 ( 
 ! 
 response 
 . 
 isDone 
 ()) 
  
 { 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Waiting for response..." 
 ); 
  
 Thread 
 . 
 sleep 
 ( 
 10000 
 ); 
  
 } 
  
 List<SpeechRecognitionResult> 
  
 results 
  
 = 
  
 response 
 . 
 get 
 (). 
 getResultsList 
 (); 
  
 // Just print the first result here. 
  
 SpeechRecognitionResult 
  
 result 
  
 = 
  
 results 
 . 
 get 
 ( 
 0 
 ); 
  
 // There can be several alternative transcripts for a given chunk of speech. Just use the 
  
 // first (most likely) one here. 
  
 SpeechRecognitionAlternative 
  
 alternative 
  
 = 
  
 result 
 . 
 getAlternativesList 
 (). 
 get 
 ( 
 0 
 ); 
  
 System 
 . 
 out 
 . 
 printf 
 ( 
 "Transcript : %s\n" 
 , 
  
 alternative 
 . 
 getTranscript 
 ()); 
  
 } 
 }

    Node.js

    To learn how to install and use the client library for Speech-to-Text, see Speech-to-Text client libraries . For more information, see the Speech-to-Text Node.js API reference documentation .

    To authenticate to Speech-to-Text, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      // Imports the Google Cloud client library for Beta API 
 /** 
 * TODO(developer): Update client library import to use new 
 * version of API when desired features become available 
 */ 
 const 
  
 speech 
  
 = 
  
 require 
 ( 
 ' @google-cloud/speech 
' 
 ). 
 v1p1beta1 
 ; 
 // Creates a client 
 const 
  
 client 
  
 = 
  
 new 
  
 speech 
 . 
  SpeechClient 
 
 (); 
 /** 
 * TODO(developer): Uncomment the following lines before running the sample. 
 */ 
 // const gcsUri = 'gs://my-bucket/audio.raw'; 
 // const model = 'Model to use, e.g. phone_call, video, default'; 
 // const encoding = 'Encoding of the audio file, e.g. LINEAR16'; 
 // const sampleRateHertz = 16000; 
 // const languageCode = 'BCP-47 language code, e.g. en-US'; 
 const 
  
 config 
  
 = 
  
 { 
  
 encoding 
 : 
  
 encoding 
 , 
  
 sampleRateHertz 
 : 
  
 sampleRateHertz 
 , 
  
 languageCode 
 : 
  
 languageCode 
 , 
  
 model 
 : 
  
 model 
 , 
 }; 
 const 
  
 audio 
  
 = 
  
 { 
  
 uri 
 : 
  
 gcsUri 
 , 
 }; 
 const 
  
 request 
  
 = 
  
 { 
  
 config 
 : 
  
 config 
 , 
  
 audio 
 : 
  
 audio 
 , 
 }; 
 // Detects speech in the audio file. 
 const 
  
 [ 
 response 
 ] 
  
 = 
  
 await 
  
 client 
 . 
 recognize 
 ( 
 request 
 ); 
 const 
  
 transcription 
  
 = 
  
 response 
 . 
 results 
  
 . 
 map 
 ( 
 result 
  
 = 
>  
 result 
 . 
 alternatives 
 [ 
 0 
 ]. 
 transcript 
 ) 
  
 . 
 join 
 ( 
 '\n' 
 ); 
 console 
 . 
 log 
 ( 
 'Transcription: ' 
 , 
  
 transcription 
 );

    Python

    To learn how to install and use the client library for Speech-to-Text, see Speech-to-Text client libraries . For more information, see the Speech-to-Text Python API reference documentation .

    To authenticate to Speech-to-Text, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

      from 
  
 google.cloud 
  
 import 
 speech 
 client 
 = 
 speech 
 . 
 SpeechClient 
 () 
 audio 
 = 
 speech 
 . 
  RecognitionAudio 
 
 ( 
 uri 
 = 
 "gs://cloud-samples-tests/speech/Google_Gnome.wav" 
 ) 
 config 
 = 
 speech 
 . 
  RecognitionConfig 
 
 ( 
 encoding 
 = 
 speech 
 . 
 RecognitionConfig 
 . 
 AudioEncoding 
 . 
 LINEAR16 
 , 
 sample_rate_hertz 
 = 
 16000 
 , 
 language_code 
 = 
 "en-US" 
 , 
 model 
 = 
 "video" 
 , 
 # Chosen model 
 ) 
 operation 
 = 
 client 
 . 
  long_running_recognize 
 
 ( 
 config 
 = 
 config 
 , 
 audio 
 = 
 audio 
 ) 
 print 
 ( 
 "Waiting for operation to complete..." 
 ) 
 response 
 = 
 operation 
 . 
 result 
 ( 
 timeout 
 = 
 90 
 ) 
 for 
 i 
 , 
 result 
 in 
 enumerate 
 ( 
 response 
 . 
 results 
 ): 
 alternative 
 = 
 result 
 . 
 alternatives 
 [ 
 0 
 ] 
 print 
 ( 
 "-" 
 * 
 20 
 ) 
 print 
 ( 
 f 
 "First alternative of result 
 { 
 i 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Transcript: 
 { 
 alternative 
 . 
 transcript 
 } 
 " 
 )

    Additional languages

    C#: Please follow the C# setup instructions on the client libraries page and then visit the Speech-to-Text reference documentation for .NET.

    PHP: Please follow the PHP setup instructions on the client libraries page and then visit the Speech-to-Text reference documentation for PHP.

    Ruby: Please follow the Ruby setup instructions on the client libraries page and then visit the Speech-to-Text reference documentation for Ruby.

    Clean up

    To avoid incurring charges to your Google Cloud account for the resources used in this tutorial, either delete the project that contains the resources, or keep the project and delete the individual resources.

    Delete the project

    The easiest way to eliminate billing is to delete the project that you created for the tutorial.

    To delete the project:

    1. In the Google Cloud console, go to the Manage resources page.

      Go to Manage resources

    2. In the project list, select the project that you want to delete, and then click Delete .
    3. In the dialog, type the project ID, and then click Shut down to delete the project.

    Delete instances

    To delete a Compute Engine instance:

    1. In the Google Cloud console, go to the VM instances page.

      Go to VM instances

    2. Select the checkbox for the instance that you want to delete.
    3. To delete the instance, click More actions , click Delete , and then follow the instructions.

    Delete firewall rules for the default network

    To delete a firewall rule:

    1. In the Google Cloud console, go to the Firewall page.

      Go to Firewall

    2. Select the checkbox for the firewall rule that you want to delete.
    3. To delete the firewall rule, click Delete .

    What's next

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